Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0228900
Funder
Australian Research Council
Funding Amount
$603,000.00
Summary
Testing facility for heavily loaded bridge and barrier systems. Government and industry are increasing truck masses from current single articulated 42.5 tonne trucks to 160 tonne multi-bogie trucks. This will provide Australia with over $1 billion of potential benefits and an efficient and competitive transport industry. To capture these benefits and further progress Australia's economy, considerable collaborative research on a number of fronts must be carried out investigating how bridges and b ....Testing facility for heavily loaded bridge and barrier systems. Government and industry are increasing truck masses from current single articulated 42.5 tonne trucks to 160 tonne multi-bogie trucks. This will provide Australia with over $1 billion of potential benefits and an efficient and competitive transport industry. To capture these benefits and further progress Australia's economy, considerable collaborative research on a number of fronts must be carried out investigating how bridges and barriers can perform safely when subjected to very heavy traffic and impact loads under laboratory and typical service conditions. This application seeks funds for establishing a unique hi-tech testing facility in Australia vital for advancing such infrastructure technology.Read moreRead less
Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will ....Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will be verified using available bridge datasets of QDMR and GCCC. The methodology is applicable to other bridge authorities throughout Australia and internationally to maintain ageing bridge stock. Read moreRead less